Role Overview
We are seeking a highly skilled Senior AI/ML Solutions Engineer with 4-5 years of experience to design, develop, and deploy state-of-the-art AI and machine learning solutions. The ideal candidate will play a critical role in shaping our AI/ML strategy, building robust models, and ensuring seamless integration with business applications.
Key Responsibilities
- Solution Development: Design and implement scalable AI/ML solutions to solve complex business challenges.
- Data Analysis: Preprocess, analyze, and interpret large datasets to extract actionable insights.
- Model Building: Develop, train, and fine-tune machine learning models using frameworks like TensorFlow, PyTorch, or scikit-learn.
- Integration: Work closely with software engineering teams to integrate ML models into production systems.
- Performance Optimization: Continuously monitor and optimize model performance to ensure accuracy and efficiency.
- Collaboration: Collaborate with cross-functional teams, including data scientists, product managers, and stakeholders, to align solutions with business goals.
- Research & Innovation: Stay updated on the latest AI/ML trends and technologies to propose innovative approaches.
- Documentation: Create detailed documentation for processes, models, and systems to ensure clarity and knowledge sharing.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- 4-5 years of experience in designing and implementing AI/ML solutions.
- Proficiency in programming languages such as Python, R, Java or JavaScript.
- Strong experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud for AI/ML deployments.
- Solid understanding of data structures, algorithms, and statistical methods.
- Expertise in data preprocessing and feature engineering techniques.
- Strong problem-solving skills and the ability to work independently or in a team.
- Experience with version control systems like Git.
- Familiarity with CI/CD pipelines for ML model deployment.
Preferred Skills
- Experience with Gen AI, natural language processing (NLP), computer vision, or reinforcement learning.
- Knowledge of containerization and orchestration tools like Docker and Kubernetes.
- Familiarity with big data tools such as Spark, Hadoop, or Apache Kafka.
- Strong understanding of MLOps practices and principles.
